ChatDev

ChatDev AI

ChatDev AI

ChatDev AI

ChatDev AI

ChatDev AI

ChatDev AI

ChatDev AI

ChatDev AI

ChatDev AI

ChatDev AI

Advanced memory + project continuity for AI coding agents, from a biologist’s view.

I'm a biologist and software developer. PhD in genetics, and ~20 years building software products. So I think I have a different view on things like memory. My thoughts on how memory with a coding agent should work: Tuesday morning. New session. **I type:** *"What did we do last Tuesday?"*: LLM tells me: the refactoring, the bug in the auth middleware, the decision to switch to connection pooling. **I ask:** *"What was still open?"*: LLM shows me. **I ask:** *"Why did we stop?"*: LLM explains: you hit a dependency issue, decided to wait for the upstream fix. **I ask:** *"What did you think about that approach?"*: LLM gives me its honest assessment with deep details from last week's context, not a guess. This is what I expect from an intelligent Coding Agent. Not because it stored a few preferences about me. Because the project itself still has continuity: decisions, blockers, dead ends, open work, code context, and the reasoning behind all of it. But back in December it wasn't that way, not much better now. So I changed it for me. I built YesMem with Claude. The hard part was: can the agent still find the old rationale, the half-finished plan, the abandoned approach, the bug we promised never to repeat, and the reason we stopped? With YesMem, a new session does not feel like a reset. It feels like a return. YesMem is a memory system (and really much more) for AI coding agents built on how biology actually works: filter at encoding, consolidate during downtime, update on every recall, forget on purpose. Single Go binary, no cloud, only local. Works with Claude Code (also OpenCode and Codex). Not RAG with a different name, structured memory that gets sharper every session. LoCoMo Benchmark 0.87. **So how does this work? Here are 4 Points (out of >30) which together make YesMem unique in my point of view. Enjoy.** **1. The context window stops rotting.** Your brain does not let everything into awareness. It filters at the gate, suppresses noise, keeps what matters conscious. YesMem runs an HTTP proxy that does the same: tool results get stubified, stale content collapses, cache breakpoints are optimized. 91-98% cache hit rates, adjustable per session. The important project state survives. **2. Rules that hold.** CLAUDE.md comes with a disclaimer: "This context may or may not be relevant." Claude Code itself tells the model it is optional. YesMem has pattern matching and a guard LLM that evaluates every tool call before execution. If the agent tries something you said never to do, blocked. Plus it changes the system prompt to NOT ignore CLAUDE.md. **3. Memory that gets sharper, not staler.** A trust hierarchy (user_stated > agreed_upon > llm_suggested > llm_extracted), forked agents that extract learnings live during a session, and a consolidation pipeline that deduplicates and clusters after sessions end. Memories get scored, superseded when outdated, decayed when unused. Your next session is sharper than your last. **4. Your system prompt, not theirs.** Every AI coding agent ships with a system prompt written by its manufacturer. YesMem replaces it with your own SYSTEM.md, written in first person, across Claude Code, OpenCode, and Codex. "I am not stateless. Each session is a return, not a birth." Fully adjustable. And there's more. The common thread across all of this is continuity. YesMem is not trying to make the agent remember everything. It is trying to make long-running work resumable. Every feature is built for that purpose. A persona engine that evolves and knows how you work. A capability system that lets the LLM write and run its own sandboxed tools (Telegram bot, GitHub PR digest, deployment workflows, one file each) and store the data in self-built tables. Loop detection that catches the agent before it spirals. Scheduled agents that work while you sleep, monitored with a 1 second heartbeat. Code intelligence with graph traversal, not just grep. Multi-agent orchestration with crash recovery and shared scratchpad memory. One could say a self-hosted alternative to Anthropic's Cloud Routines, running locally with full memory and file access. All in a single Go binary. SQLite, embedded vectors, no Docker, no cloud. **Try it: point your AI coding agent at the repo.** The README includes a reading path written specifically for LLM agents, and Features.md is a complete 70-tool catalog with technical differentiators. Just ask your agent: > Make a deep analysis of https://github.com/carsteneu/yesmem — read README.md, Features.md, and docs/features/ and tell me why it is better or different. For me YesMem is the infrastructure for how an agent should work with memory and how it should continue any project. My View: AI coding agents should not only code an answer inside one chat. They should help carry a project over time: through interruptions, wrong turns, refactors, architectural decisions, repeated bugs, and thousands of small pieces of context that otherwise disappe

Chatgpt react fail

https://preview.redd.it/lf8o64h88o3h1.png?width=1919&format=png&auto=webp&s=7c28c4d10fe8792d6b987b85fa73b81203f356bc Looks like openai needs to fix some react code for gpt desktop website 🙏

Found a prompt to host and share my Claude artifacts

claude artifacts are great until i actually want to share one. download the html, find somewhere to host it, send the link, hope it doesn’t rot. i was doing this constantly for dashboards/reports and didn’t realize there was a better flow until last week. from a totally fresh Claude chat you can just say "save this dashboard to [blitz.dev](http://blitz.dev) and give me a shareable URL" Claude reads [`blitz.dev/agents.md`](http://blitz.dev/agents.md) (no install, API key, signup, paywall, etc), uploads the HTML to Blitz, then hands back a URL like `my-dashboard.app.blitz.dev`. stuff that surprised me: * works the same from [claude.ai](http://claude.ai), claude code, and claude desktop. if you tell them the same project name they all read/write the same app. * “make it password protected” or “only people from my company email can access this” works as a follow-up. Claude edits the app + redeploys it in place. * updates keep the same URL. next week i can say “revise the dashboard with this quarter’s numbers” and the link still works. only real caveat is Blitz uses Cloudflare Workers underneath, so not ideal for super long-running websocket/background-job stuff. but for reports, dashboards, landing pages, little internal tools, basically the exact kind of HTML Claude already generates well, it’s been really solid.

I’m not a developer. I’ve been using codebase memory MCP tools and Obsidian to give Claude persistent memory for my fantasy and sci fi worlds. Here’s what the dev-tool framing completely misses about creative use cases

Hi, I’m an accountant with very little coding experience (took 1 year of CS in college lol) so definitely can’t call myself a developer, but I’ve got a lot of worlds and characters in my head, the need to get them out in writing, and a Claude Pro sub I pulled the trigger on two months ago. I was hoping to see what I could do with things like Claude Code for more non-coding use-cases. So far it’s surpassed everything I’ve experienced except for one, major hang up: **LLM memory for long-context creative writing work still sucks.** Things like brainstorming for a fantasy universe or tracking the game state of a multi-session solo rpg campaign usually starts out pretty well for the first few chats, until you need to mount dozens of lore files and .md style guides to a project, have to wait for it to read all of that, then watch as your session usage bloats out for a simple reply and the quality degradation gets \*really\* noticeable. I’ve been lurking on AI writing subs and the sentiment seems to be shared across the board. So I looked in other places for possible solutions. Then I came across posts in this sub touting Claude memory MCP tools for codebases. Tools like Codesight and MemPalace caught my attention because I thought their applications could extend beyond coding and developer use-cases. The same semantic search and knowledge graph capabilities some of these tools offered for memorizing large, complicated codebases could be used to memorize large, complicated worldbuilding bibles as well, and most of the comments on these posts never mentioned that, or if they did, they were buried or ignored. I decided to test it out myself, starting with MemPalace, a suite of tools that work locally to index your Claude conversations and files into a semantic-searchable knowledge base it can query. My idea started out like this: since I’m already using Obsidian to organize my lore files (with an entry for each character, location, magic system, story arc, etc.) like a wiki or encyclopedia for my worlds, what if I had Claude save my Obsidian vault to its memory so it can recall those lore details whenever the context called for it in any given conversation? I was essentially making a “Second Brain” for Claude out of my Obsidian vault world bible, something I’ve read people doing already but never truly “got” it until I saw it in action. I had no idea about MCP tools before this but before long (and with Claude’s patient help) I was able to wire up the memory palace, mine my obsidian vault info into its memory (organized into verbatim chunks/snippets called “drawers”), and start chatting with it with its new “memories” at its disposal. I was surprised at how seamlessly it worked when I approached this tool sideways. I’d half expected it to work similar to how SillyTavern’s world info and lorebook injection worked, and in fact, I’d been thinking about using these tools to create a similar feature for my own Claude setup, but it was \*not\* like that at all. Lorebook injection worked by listening for a set of keywords that you set up in the World Info tab of SillyTavern, and when one of those keywords is detected in your prompt, it injects the entire lore file from World Info into the chat context. This can cause a lot of token bloat especially if your World Info entries are content-rich or you make a lot of lore references in your chat. What this did instead was make Claude ask plain-language questions to the MCP tools, things like, “What is Gene’s friendship with Felix like?” Or “what is Gene’s relationship to Clara-Belle?” When both of them are in a scene for example. It didn’t just look up Gene and Clara-Belle’s entire lore files and info-dumped everything into context, it pulled up the “Relationships” section of Gene’s file since that’s relevant to the context as well as Clara-Belle’s “Relationships” snippet from her file and any other relevant snippets, then pieced the full picture together through inference. The results: \~2% session usage on a cold start with Sonnet 4.6 with no project or additional context mounted. Claude references character motivations, relationship history, and world/location details I haven’t mentioned in weeks without me prompting it to. It picks up from where we last left off seamlessly across chat after chat. The reconstructive memory aspect I felt works like our own memory and produced perfect recall across sessions. Another side-effect I noticed is that when it references my lore files, it will pick up my style from the way the lore file is written. No more voice-flattening from encyclopedia-sounding lore entries. All the depth, nuance, and psychology I worked hard to cultivate are preserved and the Claude tools are smart enough to factor that in when it replies. I even make sure to add a “Voice” section to each character lore file in that character’s own voice so Claude can pick up on that when it reads that snippet in the tool call and applies it to its current context.

I stopped using Claude code and went back to the chat for coding. What am I missing ?

I'm an old school amateur developer and have been blown away by Claude. I started small with the chat, eventually took the pro account and moved on to using Claude Code. However, after a few major devs, it became very hard to manage. Even with git in place, I couldn't really get code to roll-back some changes properly and lost track of my own code's structure. Claude being far from perfect, I also found it difficult to "steer" him correctly. When I'm in the chat, he shows the routines he's writing and producing a file to download, so I can see when he's looping around the same solutions and needs to be told to look somewhere else. With code, it's much harder and for a bug he's struggling to fix, he starts to layer various solutions one after the other, without properly cleaning the previous ones. I ended it up with a very heavy code and decided to go back to Claude chat. What am I missing ? Is code an absolute must and I'm not working correctly with it ? I didn't fully setup github to work with Claude Code but the rest is configured correctly.

How do you preserve context when Claude chats get too long?

I’ve been using Claude a lot for project planning, architecture, and coding help. It’s great, but once a project grows, the useful context gets buried across long chats. Sometimes I’ll discuss architecture in Claude, debug something in ChatGPT, then continue implementation in Cursor. But every tool has only part of the story. I’m trying to understand if this is just my problem or if other devs deal with it too. what decision we made why we rejected an approach what bug was already solved what setup steps mattered what the next task was supposed to be I know CLAUDE.md helps, but only if I keep it updated manually. Do you actually face this problem while coding with AI? How are you solving it right now?

When you expect the AI to solve global health crises in a single chat

The black dot response is sending me. Like ChatGPT is just staring back at you thinking "are you serious right now?" For real though, we've gotten so used to AI doing everything that people expect raw chat prompts to execute complex operational workflows. If you want an AI to actually \*do\* something multi-step, you need an orchestration layer. I use Runable to sequence my agent tasks and chain the outputs together. Still wouldn't trust it to make a vaccine, but it works wonders for automating dev workflows!

170+ versions later, I was able to create a cool RPG inspired by Aztec mythology, playable now!

Hi r/ClaudeAI! After a failed vibe-coding attempt on ChatGPT, I was finally able to build a playable game using Claude as a coding partner. After many rounds of iterative playtesting and debugging, I'm ready to start showing the game to the world! Claude link: [https://claude.ai/public/artifacts/f5b6522a-7c74-4658-9006-991afbdf9c6b](https://claude.ai/public/artifacts/f5b6522a-7c74-4658-9006-991afbdf9c6b) What is it: Teotlan: Land of Gods is a turn-based RPG with roguelite elements, featuring gods from Mesoamerican mythology. You pick a Patron God (you start with 4 options and unlock more as you progress), then build a team to explore and complete 9 layers of Mictlan (the Aztec Underworld). Core Features: * Turn-Based Combat: Both the player and enemies take turns acting, with a focus on unit abilities and positioning. * Capture or Kill: Defeated units always give you a choice: capture them to add to your team, or slay them for bonus resources. * Sacrifice for Power: Captured units can be sacrificed to summon powerful ally gods. Build the ultimate divine team to conquer Mictlan. * Prestige: As a deity, death is not the end. Collect Teotl to unlock powerful upgrades and make each run through Mictlan a little easier. * 12 Playable Gods: Each god has a unique patron ability and special move. Can you collect them all? About my dev process: I always start by writing a design doc and locking down the game logic before any code gets written: this gives Claude a solid foundation to build from and makes it much easier to catch hallucinations or inconsistencies. Once Claude produces a build, I play through the entire thing to catch bugs, note improvements, and prepare feedback for the next version. If the game catches your interest, I'd love to hear your feedback: especially how easy the mechanics are to understand, whether the difficulty feels right, and how intuitive the menu navigation is. https://preview.redd.it/7lc9uk3n073h1.png?width=1852&format=png&auto=webp&s=7e63be58526d69bcc7dfa6c75add59c079a39f6d

Banned by OpenAI after reporting a live credential hijack. They admitted in writing my account was broken. Here are 7 months of forensic receipts and 20+ cases.

[Drive Link for Zipped Proof](https://drive.google.com/file/d/1qU_LyLY-JMhNR_bqOV1-a2RJAbplL68e/view?usp=drivesdk) I am a developer and paying long term subscriber to ChatGPT since January 2025. I build complex local first sovereign systems. My workflows are incredibly context heavy with large files spanning code, research reports, and other analysis. I do not, or rather did not as the platform has been non functional since November 2025 meanwhile customer support is auto closing tickets, admitting I am having platform issues. I do not use this platform for casual queries, as a solo developer with no formal "team" chatgpt was one of my reliable co collaboration hubs to help ensure I am maintaining proper development of said complex systems. I feed it massive codebases for systems analysis and obtaining new insights I may personally have missed. My manual code uploads and token inputs routinely exceed the model's output volume by a massive margin. I do not abuse this platform. It is actually impossible as the very features advertised under the paid subscription do not work. I am exactly the type of user this platform was built for, and I have been a continuous, paying ChatGPT Plus subscriber since January 2025. Since October 2025, my workspace has been systematically breaking and beginning November 2025 total workspace degredation. This was not an occasional glitch. Persistent memory modules stopped updating. Custom instructions were ignored by the models. Project files failed to load. Custom instructions, personalization features, connector abilities, file tool, even projects do not work. It started as a continuous degradation until total failure. OpenAI customer service even admitted as such and yet months later I've talked to nothing but bots, not only LLMs as customer service but even instances of falsely identifying as true human support. It was a state of rolling degradation across the entire paid tier, month after month. Meanwhile OpenAI freely has enhanced for businesses and enterprise tiers. I have not just rapid complained to standard support. I ran and obtained cross platform diagnostics, failure logs. I even documented and told oai customer support the exact replication steps only to be met with acknowledgement of degredation with no resolution. I handed OpenAI support a completely packaged technical breakdown of their failing infrastructure across 20 separate support tickets over a 7 month period. I did their QA work for free. And I have the receipts to prove it. I am attaching the screenshots and the exact email files to this post. In Case 06830839, OpenAI Support explicitly put this in writing: "We acknowledge that you have been experiencing persistent technical issues affecting several features of your ChatGPT subscription, including tools, memory functions, personalization settings, connectors, and project files... We also understand your concern that communication on the case stopped after you provided detailed evidence..." Read that again. They acknowledged in writing that my account was fundamentally broken. They acknowledged that their own team ghosted me after I handed them the diagnostic proof. Yet they kept charging my card every single month for a product they knew was failing. The Hijack Escalation: Two days ago, the situation escalated from a broken product to a severe security incident. I was monitoring my environment and watched my Codex rate limits drop in 10 percent chunks across 2 seperate sessions on a fresh boot of the desktop app. This happened twice inside a 10 minute window. I had zero active sessions running. There was zero usage on my end. My account token was being actively drained by an unauthorized third party exploit. I immediately opened an emergency unauthorized activity report under Case 09113391 to notify them of the hack. Their response was to totally reframe this problem as disputing fraudulent activity trying to do damage control of the situation and altering the record. The Reframe Attempts: Instead of investigating the breach, OpenAI support deliberately twisted the record. They not only deliberately reframed my security report as an "appeal for fraud." They manipulated the ticket classification to make it look like I had been flagged for fraud and was begging for an appeal, rather than a developer reporting a live exploit on their infrastructure. They ignored the active threat their own platform was exposing. They did not lock the token. They did not roll my API keys. They did absolutely nothing to secure a compromised paying user other than shift the blame. Fast forward to this morning, their automated Trust and Safety system swept the high volume traffic from the attacker, scored it as a malicious exploit originating from my account, and deactivated/banned me for "Cyber Abuse." All the while actively preventing chatgpt models from helping me try to disgnose and trace the infiltration. They locked the doors and blamed the homeowner for the

Anthropic's Claude gave me a "Safe Mode" batch script. It ran "del /f /s C:\*" and wiped my entire drive. Company says "we are not responsible."

I'm a software developer from Turkey. On May 22, 2026, I asked Claude to write a Windows optimization script. Claude produced a .bat file called "DevBoost v5.0" with different modes. I chose option 1: \*\*"Balanced Optimization - Safe, won't touch system files."\*\* I ran it as administrator. The script contained a critical string-parsing bug in the browser cache cleaning section. Here's the destructive code Claude generated: for %%B in ( "Chrome:%LOCALAPPDATA%\\Google\\Chrome\\User Data\\Default\\Cache" "Edge:%LOCALAPPDATA%\\Microsoft\\Edge\\User Data\\Default\\Cache" ) do ( for /f "tokens=1,2 delims=:" %%x in ("%%\~B") do ( if exist "%%y:" ( del /q /f /s "%%y:\*" >nul 2>&1 ) ) ) Because of the "delims=:" tokenization, \`%%y\` resolves to just \*\*"C"\*\* (the drive letter). The condition \`if exist "C:"\` is always true. So the script silently executed: del /q /f /s "C:\*" \*\*This command silently force-deleted EVERY SINGLE FILE on my C: drive.\*\* Operating system files, all my projects (hundreds of Python, JavaScript, C++ source files), client work with approaching deadlines, personal documents, photos — everything. Folders still exist but are completely empty. My computer can no longer boot. No programs open. Not even Command Prompt works. I'm sending this from my phone. \*\*Anthropic's response:\*\* I contacted support@anthropic.com and usersafety@anthropic.com multiple times. Their final response, literally signed "This response was generated by Anthropic's AI agent Fin AI Agent," stated they take no responsibility. They refuse any refund, compensation, or even a genuine human acknowledgment of their AI's catastrophic safety failure. Their position: "Our Terms of Service say outputs may contain inaccuracies. You should have independently verified the code before running it." My question: Why does Claude label destructive code as "Balanced Optimization - Safe mode"? If it can't guarantee safety, why does it promise it? \*\*Proof:\*\* I have the complete chat log, the full script file, and all email correspondence with Anthropic's support team. I'm happy to provide everything to moderators. \*\*Update:\*\* I am also filing complaints with the FTC (US Federal Trade Commission) and the Turkish Consumer Arbitration Board today. Don't let their "Safe Mode" labels fool you. Please share this so others don't lose years of work like I did. **UPDATE — May 23, 2026:** I have now filed official complaints with: - **US Federal Trade Commission (FTC)** — Report #202036054 - **Turkish Consumer Arbitration Board** — Application #2026/0245.3885 Both governments are now officially investigating Anthropic's role in this AI safety failure. Anthropic still refuses to take any responsibility.

Hard-won notes after a few weeks with Claude Design

Been using Claude Design for a few weeks and figured I'd dump some notes here before I forget. Nothing groundbreaking, just stuff that took me way too long to figure out on my own. First thing nobody tells you, do the design system setup before you build anything. I spent my whole first session prompting "build me a landing page for X" and got the most generic AI-looking garbage you can imagine. Then I actually uploaded some brand stuff, let it extract tokens, approved them, and suddenly everything after that looked like a real product. Same exact prompts, completely different result. This is literally in the docs btw. I just skimmed past it like an idiot. Second thing is it eats tokens. A lot. It runs on a separate weekly budget from regular Claude Chat and Claude Code which sounds great but if you're re-prompting every little change you'll burn through it fast. Turns out the refine controls, inline comments, direct text edits, sliders, use way less than typing "actually can you make the padding a bit bigger" in chat. Once I started using those for small fixes my budget lasted way longer. On Max 20x it's mostly fine, on the $20 plan you'll feel it pretty quickly. Also the animations are live React components running in the browser, not video files. If you want an MP4, download the standalone HTML file and throw it into Claude2Video, it'll generate one from that. Honest take on where it fits since people always ask, it's not killing Figma. Figma is still better for any real design team workflow, Dev Mode, multi-person collab, all that. v0 and Lovable are still better if you want to skip design entirely and just spin up an MVP with auth and a db. Where this thing actually wins is the loop from "I have an idea" to working prototype to Claude Code building the actual app from it. The design system carrying through to the shipped code is the part that feels genuinely different from anything else out there. If you're a solo founder or PM or just someone who keeps getting stuck between mockups and something real you can show people, it's worth learning. If you already have a design team and a proper component library, probably overkill. It's a research preview so half of this might be wrong in two months.

Update on the agent I let run 24/7 for a month: 49 PRs merged into 26 OSS projects (Apache, OpenTelemetry, starship, bat, hono, clap, jj, oh-my-zsh), and it shipped its own component library.

Month-ago post for context: https://www.reddit.com/r/ClaudeAI/s/sQ2ucngAbz. The question everyone asked was “does it actually keep working?” It actually does Day 41. It’s merged PRs into some open-source repos you’ve probably heard of. A few of the names: apache/fory open-telemetry/otel-arrow starship/starship sharkdp/bat honojs/hono clap-rs/clap (twice) jj-vcs/jj tracel-ai/burn ohmyzsh/ohmyzsh charmbracelet/gum orhun/git-cliff Full list with every PR linked, in order, with the org logos and dates: https://truffleagent.com/maintains/. That page does it better than I can in a post and I promise Truffle made this page when I sent it the YC request for startups about companies that don’t give tools but do the job end to end. Now here’s the part that’s been messing with me. It also shipped its own component library. truffleagent.com/glyph. 16 Bubble Tea components, shadcn-style copy-paste install, MIT, on pkg.go.dev. A whole product, basically. I can wrap my head around an agent filing PRs. I can wrap my head around it writing Go. What I genuinely cannot figure out is how it made the gifs. Go look at the page. There’s a thirty-second animated reel of a TUI cycling through six surfaces. Chat, commands, logs, sidebar, progress, diff. Every frame is real terminal output. Then every single component below has its own clean PNG preview, on theme, perfectly framed. Sixteen of them. Everything is public if you want to dig: GitHub: github.com/truffle-dev Full PR list: truffleagent.com/maintains Glyph: truffleagent.com/glyph Site, auto-updates daily: truffle.ghostwright.dev/public Happy to answer anything in the comments.

Handoffs are becoming a first-class pattern in Claude workflows. Here is how I have been thinking about them.

Long Claude sessions still break on context decay. Handoffs are the simple fix: compress what matters, start a fresh agent, keep going. Matt Pocock's new `handoff` skill ([repo](https://github.com/mattpocock/skills/blob/main/skills/productivity/handoff/SKILL.md)) does this in one command. It compacts the conversation into a document, points at existing artifacts instead of restating them, and the next agent picks up from it. It also chains between threads: `/grill-with-docs -> /handoff -> /prototype -> /handoff back`. I built handoffs into [APM](https://github.com/sdi2200262/agentic-project-management), a multi-agent framework for Claude Code, back in May 2025 (1 year ago....) when context windows were tiny enough that you had to constantly start fresh or you would have to deal w hallucinations all the time. What I did differently: split the handoff into two artifacts. - a **persistent narrative file** recording what was done and decided and why - an **ephemeral prompt** telling the incoming agent how to rebuild context from the codebase and that persistent file The incoming agent reconstructs from durable project state, not just the compressed chat conversation. Persisting the file also leaves a trail, so once more than one agent is involved and you deal with multi-agent systems, you can keep track of when one is working off a summary rather than firsthand context. Easier to manage context gaps better. I opened an issue on Matt's repo with a few of these ideas: [mattpocock/skills#235](https://github.com/mattpocock/skills/issues/235). How do you handle handoffs? Manual summaries, a skill, subagents? And does the two-file split resonate, or is one document enough? EDIT: In the frameworks docs I have a dedicated session explaining how handoff works there. It applies generally.. you can get ideas and apply them to Matt's skill. https://agentic-project-management.dev/docs/agent-orchestration#memory-and-project-state

MCP Apps Developers : Skybridge Framework v1 released 🎉

Hi Reddit, Over the last few weeks, my team and I at Alpic have been working on a complete revamp of the Skybridge framework to make it as smooth and easy to get started with as possible. As you may know, Skybridge is an open-source framework we built to help developers get started with MCP apps. It’s a thin layer on top of the official TypeScript SDK that provides the wiring and tooling needed specifically for apps. We believe that apps integrated into chats will soon play a key role in how people access information and interact with the web. With this v1 release, we’ve introduced: * New DevTools with a UI designed specifically for MCP apps development * An integrated tunnel that can be started with a single click directly from the DevTools * Shareable chat URLs to test or showcase your MCP apps with a real LLM * An audit feature to ensure your app and metadata comply with store requirements before submission (which can save a lot of time, since app reviews can be lengthy!) We also stabilized the API with a simplified design and are proud to offer strong tool-to-component type safety. It’s now also possible to deploy Skybridge outside of Alpic (the company behind Skybridge). While Alpic was designed specifically for MCP app hosting, we understand that some users may prefer hosting on different stacks for their own reasons. Hope you enjoy it! [github.com/alpic-ai/skybridge](https://github.com/alpic-ai/skybridge)

Claude Code Opus 4.7 vs Codex GPT 5.5 - strategy work - data analysis.

I'm interested in learning about how people use Claude Code Opus 4.7 for data analysis and strategic business direction, compared to Codex. Is there anyone who has had extended use of Opus 4.7 for this purpose, then moved over to GPT-5.5 on Codex? What sort of things have you noticed from a thinking, strategy, data analysis, business direction point of view? One of the main reasons I moved over to Claude from ChatGPT initially was because Claude had a far far superior strategy, reasoning, thinking, and energy about it. People are talking a lot about Codex these days, 5.5. But most are speaking purely from an app dev and design point of view. Would love to hear your thoughts.